STUDY OF MAXIMUM POWER POINT TRACKING ALGORITHMS FOR EFFICIENCY GROWTH OF PHOTOVOLTAIC CELLS

Subject of Research.The paper considers simulation model of the electro generating installation based on photovoltaic converters. It is known that photovoltaic cells have rather low conversion efficiency of energy therefore performance improving of the designed energy system can be partially reached by means of controlled intermediate converters. The main goal of this paper is model implementation of a solar power system and also comparative analysis of the different maximum power point tracking algorithms which are used to control energy system with the purpose to increase power efficiency of all system. Method. All algorithms considered in the paper are based on the search for an extremum on the volt-power characteristic of a photovoltaic converter. Implementation of the most popular methods of maximum power point tracking is considered: "Perturbation and observation" and "Increasing conductivity". An algorithm based on the theory of fuzzy logic is proposed for application aimed at the growth of photovoltaic cells efficiency as an alternative method for traditional algorithms. Main Results. The model of solar panel control system is implemented in MATLAB/Simulink. Three methods for maximum power point tracking within this photovoltaic system are considered and implemented. Comparative analysis of operation of different control algorithms is carried out for different levels of solar radiation intensity. Practical Relevance. The algorithms can be implemented in real power systems for improvement of their overall performance

Dynamic Slice of Aspect Oriented Program A Comparative Study

Aspect Oriented Programming (AOP) is a budding latest technology for separating crosscutting concerns . It is very difficult to achieve cross cutting concerns in object - oriented programming (OOP). AOP is generally suitable for the area where code scattering and code tangling arises. Due to the specific features of AOP language such as joinpoint, point - cut, advice and introduction, it is difficult to apply existing slicing algorithms of procedural or object - oriented programming directly to AOP. This paper addresses different types of program slicing approaches for AOP by considering a very simple example. Also this paper addresses a new approach to calculate the dynamic slice of AOP. The complexity of this algorithm is better as compared to some existing algorithms

A Survey of Protocol-Level Challenges and Solutions for Distributed Energy Resource Cyber-Physical Security

The increasing proliferation of distributed energy resources (DERs) on the smart grid has made distributed solar and wind two key contributors to the expanding attack surface of the network; however, there is a lack of proper understanding and enforcement of DER communications security requirements. With vendors employing proprietary methods to mitigate hosts of attacks, the literature currently lacks a clear organization of the protocol-level vulnerabilities, attacks, and solutions mapped to each layer of the logical model such as the OSI stack. To bridge this gap and pave the way for future research by the authors in determining key DER security requirements, this paper conducts a comprehensive review of the key vulnerabilities, attacks, and potential solutions for solar and wind DERs at the protocol level. In doing so, this paper serves as a starting point for utilities, vendors, aggregators, and other industry stakeholders to develop a clear understanding of the DER security challenges and solutions, which are key precursors to comprehending security requirements

A Low Complexity Active Sensing and Inspection System for Monitoring of Moveable Radiation Environments

Due to the portable property of moveable radiation sources, the traditional monitoring method is becoming increasingly unsuitable and it is urgent to provide an effective and low-cost method. This paper presents an active monitoring scheme for moveable radiation environments, the in situ monitoring, including a radiation detection node, an infrared proximity node, and an alarm node; these three schemes communicate with each other through the ZigBee wireless network. An active monitoring mechanism which realizes the automatic judgment of radiation source inbound or outbound state is proposed, thereby automatically switching the data sampling mode under different working conditions, so as to reduce the energy consumption of nodes. Based on the mobile terminal client application to interact with the monitoring center, a collaborative management mode between enterprise users and the environmental protection department is realized. A testbed of a simple active sensing and inspection system is created to test its user interaction capabilities. Experimental results prove that the system schedule proposed can effectively detect and dynamically monitor the moveable radiation source. The system can be easily replicated and extended to more environmental monitoring network

Wind generation forecasting methods and proliferation of artificial neural network:A review of five years research trend

To sustain a clean environment by reducing fossil fuels-based energies and increasing the integration of renewable-based energy sources, i.e., wind and solar power, have become the national policy for many countries. The increasing demand for renewable energy sources, such as wind, has created interest in the economic and technical issues related to the integration into the power grids. Having an intermittent nature and wind generation forecasting is a crucial aspect of ensuring the optimum grid control and design in power plants. Accurate forecasting provides essential information to empower grid operators and system designers in generating an optimal wind power plant, and to balance the power supply and demand. In this paper, we present an extensive review of wind forecasting methods and the artificial neural network (ANN) prolific in this regard. The instrument used to measure wind assimilation is analyzed and discussed, accurately, in studies that were published from May 1st, 2014 to May 1st, 2018. The results of the review demonstrate the increased application of ANN into wind power generation forecasting. Considering the component limitation of other systems, the trend of deploying the ANN and its hybrid systems are more attractive than other individual methods. The review further revealed that high forecasting accuracy could be achieved through proper handling and calibration of the wind-forecasting instrument and method

Fractional-Order PID Controllers for Temperature Control:A Review

Fractional-order proportional integral derivative (FOPID) controllers are becoming increasingly popular for various industrial applications due to the advantages they can offer. Among these applications, heating and temperature control systems are receiving significant attention, applying FOPID controllers to achieve better performance and robustness, more stability and flexibility, and faster response. Moreover, with several advantages of using FOPID controllers, the improvement in heating systems and temperature control systems is exceptional. Heating systems are characterized by external disturbance, model uncertainty, non-linearity, and control inaccuracy, which directly affect performance. Temperature control systems are used in industry, households, and many types of equipment. In this paper, fractional-order proportional integral derivative controllers are discussed in the context of controlling the temperature in ambulances, induction heating systems, control of bioreactors, and the improvement achieved by temperature control systems. Moreover, a comparison of conventional and FOPID controllers is also highlighted to show the improvement in production, quality, and accuracy that can be achieved by using such controllers. A composite analysis of the use of such controllers, especially for temperature control systems, is presented. In addition, some hidden and unhighlighted points concerning FOPID controllers are investigated thoroughly, including the most relevant publications

Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data